Hypoxia occurs in 80% of non-small cell lung carcinoma (NSCLC) cases, leading to treatment resistance. Hypoxia’s effects on NSCLC energetics are not well-characterized. We evaluated changes in glucose uptake and lactate production in two NSCLC cell lines under hypoxia in conjunction with growth rate and cell cycle phase distribution. The cell lines A549 (p53 wt) and H358 (p53 null) were incubated under hypoxia (0.1% and 1% O₂) or normoxia (20% O₂). Glucose and lactate concentrations in supernatants were measured using luminescence assays. Growth kinetics were followed over seven days. Cell nuclei were stained with DAPI and nuclear DNA content was determined by flow cytometry to determine cell cycle phase. Gene expression under hypoxia was determined by RNA sequencing. Glucose uptake and lactate production under hypoxia were greater than under normoxia. They were also significantly greater in A549 compared to H358 cells. Faster energy metabolism in A549 cells was associated with a higher growth rate in comparison to H358 cells under both normoxia and hypoxia. In both cell lines, hypoxia significantly slowed down the growth rate compared to proliferation under normoxic conditions. Hypoxia led to redistribution of cells in the different cycle phases: cells in G1 increased and the G2 population decreased. Glucose uptake and lactate production increase under hypoxia in NSCLC cells indicated greater shunting of glucose into glycolysis rather than into oxidative phosphorylation compared to normoxia, making adenosine triphosphate (ATP) production less efficient. This may explain the redistribution of hypoxic cells in the G1 cell cycle phase and the time increase for cell doubling. Energy metabolism changes were more prominent in faster-growing A549 cells compared to slower-growing H358 cells, indicating possible roles for the p53 status and inherent growth rate of different cancer cells. In both cell lines, genes associated with cell motility, locomotion and migration were upregulated under chronic hypoxia, indicating a strong stimulus to escape hypoxic conditions.

Hypoxia-induced radioresistance reduces the efficacy of radiotherapy for solid malignancies, including non-small cell lung cancer (NSCLC). Cellular hypoxia can confer radioresistance through cellular and tumor micro-environment adaptations. Until recently, studies evaluating radioresistance secondary to hypoxia were designed to maintain cellular hypoxia only before and during irradiation, while any handling of post-irradiated cells was carried out in standard oxic conditions due to the unavailability of hypoxia workstations. This limited the possibility of simulating in vivo or clinical conditions in vitro. The presence of molecular oxygen is more important for the radiotoxicity of low-linear energy transfer (LET) radiation (e.g., X-rays) than that of high-LET carbon (¹²C) ions. The mechanisms responsible for ¹²C ions’ potential to overcome hypoxia-induced radioresistance are currently not fully understood. Therefore, the radioresistance of hypoxic A549 NSCLC cells following exposure to X-rays or ¹²C ions was investigated along with cell cycle progression and gene expression by maintaining hypoxia before, during and after irradiation. A549 cells were incubated under normoxia (20% O₂) or hypoxia (1% O₂) for 48 h and then irradiated with X-rays (200 kV) or ¹²C ions (35 MeV/n, LET ~75 keV/µm). Cell survival was evaluated using colony-forming ability (CFA) assays immediately or 24 h after irradiation (late plating). DNA double-strand breaks (DSBs) were analyzed using γH2AX immunofluorescence microscopy. Cell cycle progression was determined by flow cytometry of 4′,6-diamidino-2-phenylindole-stained cells. The global transcription profile post-irradiation was evaluated by RNA sequencing. When hypoxia was maintained before, during and after irradiation, hypoxia-induced radioresistance was observed only in late plating CFA experiments. The killing efficiency of ¹²C ions was much higher than that of X-rays. Cell survival under hypoxia was affected more strongly by the timepoint of plating in the case of X-rays compared to ¹²C ions. Cell cycle arrest following irradiation under hypoxia was less pronounced but more prolonged. DSB induction and resolution following irradiation were not significantly different under normoxia and hypoxia. Gene expression response to irradiation primarily comprised cell cycle regulation for both radiation qualities and oxygen conditions. Several PI3K target genes involved in cell migration and cell motility were differentially upregulated in hypoxic cells. Hypoxia-induced radioresistance may be linked to altered cell cycle response to irradiation and PI3K-mediated changes in cell motility and migration in A549 cells rather than less DNA damage or faster repair.

Cellular hypoxia, detectable in up to 80% of non-small cell lung carcinoma (NSCLC) tumors, is a known cause of radioresistance. High linear energy transfer (LET) particle radiation might be effective in the treatment of hypoxic solid tumors, including NSCLC. Cellular hypoxia can activate nuclear factor κB (NF-κB), which can modulate radioresistance by influencing cancer cell survival. The effect of high-LET radiation on NF-κB activation in hypoxic NSCLC cells is unclear. Therefore, we compared the effect of low (X-rays)- and high (¹²C)-LET radiation on NF-κB responsive genes’ upregulation, as well as its target cytokines’ synthesis in normoxic and hypoxic A549 NSCLC cells. The cells were incubated under normoxia (20% O₂) or hypoxia (1% O₂) for 48 h, followed by irradiation with 8 Gy X-rays or ¹²C ions, maintaining the oxygen conditions until fixation or lysis. Regulation of NF-κB responsive genes was evaluated by mRNA sequencing. Secretion of NF-κB target cytokines, IL-6 and IL-8, was quantified by ELISA. A greater fold change increase in expression of NF-κB target genes in A549 cells following exposure to ¹²C ions compared to X-rays was observed, regardless of oxygenation status. These genes regulate cell migration, cell cycle, and cell survival. A greater number of NF-κB target genes was activated under hypoxia, regardless of irradiation status. These genes regulate cell migration, survival, proliferation, and inflammation. X-ray exposure under hypoxia additionally upregulated NF-κB target genes modulating immunosurveillance and epithelial-mesenchymal transition (EMT). Increased IL-6 and IL-8 secretion under hypoxia confirmed NF-κB-mediated expression of pro-inflammatory genes. Therefore, radiotherapy, particularly with X-rays, may increase tumor invasiveness in surviving hypoxic A549 cells.

Microglia are highly motile cells that play a crucial role in the central nervous system in health and disease. Here we show that actin depolymerizing factors ADF and Cofilin1 (Cfl1) are key factors of microglia integrity and function. We found a profound morphological phenotype in absence of ADF and Cfl1 in microglia. In vivo two-photon imaging of microglia with ADF/Cfl1-KO revealed reduced microglial fine processes motility and impaired microglia migration towards a laser-induced lesion. We found increased accumulation of stabilized F-actin and altered microtubule dynamics in ADF/Cfl1-KO microglia, indicating that ADF/Cfl1 are necessary for microglial cytoskeleton dynamics. Interestingly, microglial ADF/Cfl1-deficiency decreased learning and memory, suggesting that impaired microglial cytoskeleton dynamics affect neuronal functions relevant for cognition. Our results reveal a fundamental role of ADF/Cfl1 in microglia function and underscore the importance of these innate immune cells for higher cognitive functions.

Modern fluorescence and multiphoton microscopy workflows operate within a heterogeneous ecosystem of file formats, partially overlapping metadata standards, and reader-specific conventions. In practice, this frequently leads to silent axis misinterpretations, loss or corruption of physical voxel size information, and laboratory-specific glue code that is fragile, poorly documented, and difficult to reproduce. OMIO, short for Open Microscopy Image I/O, addresses these issues by providing a lightweight, policy-driven image I/O layer for Python that enforces a canonical, OME-compatible data representation at the API boundary. The central contribution of OMIO is the explicit separation of low-level format access from semantic normalization. Existing reader libraries are used as interchangeable backends for extracting pixel data and available metadata, while OMIO enforces axis conventions, metadata interpretation, and fallback decisions in a centralized and auditable policy layer. This design allows heterogeneous microscopy inputs to be converted into a stable representation without propagating backend-specific assumptions into downstream analysis code. The core design principles of OMIO include canonical axis semantics (TZCYX), robust metadata normalization with explicit and auditable fallbacks, memory-aware operation via optional Zarr-based backends, and workflow-level semantics that extend beyond individual files to folder stacks and BIDS-like project structures. This architecture allows OMIO to orchestrate existing reader libraries into a coherent and reproducible I/O pipeline without replacing or duplicating their functionality. OMIO is implemented as an open-source and community-oriented system in which support for additional file formats and metadata conventions can be added incrementally through modular reader backends. By encouraging the contribution of example datasets, backend extensions, and feature requests, OMIO is designed to evolve alongside emerging acquisition systems while preserving strict semantic guarantees at the interface level. The resulting standardized OME-TIFF outputs are immediately suitable for downstream quantitative analysis and interactive inspection in scientific Python workflows, including workflows based on ImageJ and Napari.

Quantitative cell colocalization in fluorescence microscopy often depends on ad hoc combinations of image loading, segmentation, region selection, manual inspection, and spreadsheet post-processing. Such workflows are difficult to transfer across projects and often obscure how intermediate results were produced. We present CellColoc, an open-source Python workflow pipeline for segmentation-based cell colocalization, single-channel segmentation, and cell feature extraction in 2D and 3D microscopy images. CellColoc provides a modular workflow layer that integrates existing segmentation backends, including Cellpose and threshold-based methods, into reusable, script-driven analyses. The package supports channel-wise backend selection, interactive or reusable regions of interest, optional third-channel occupancy and cell-positivity analysis, z-cropping and z-projection, cached post hoc refinement of Cellpose thresholds, and reanalysis after manual mask editing. Analyses are executed from concise user scripts while reusable functionality is kept in a core package. Intermediate artifacts such as ROI masks, per-channel label masks, positive-cell masks, and structured result tables are written to a standardized results directory, promoting transparent inspection, reproducibility, and FAIR-aligned reuse. Public example datasets, a synthetic benchmark, and archived software releases accompany the package. By separating reusable analysis logic from project-specific configuration, CellColoc offers an extensible foundation for community-driven microscopy workflows that need transparent per-cell overlap classification, morphology readouts, and reusable batch analysis.